
Learn from integration and AI leaders and practitioners across industries what it took to transform data engineering and integration, and succeed with AI.
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Catch up on the highlights, dive into the sessions you missed, and get a real taste of the experience. It’s the perfect way to see what’s in store — and trust us, this year is going to be even more unforgettable. Watch 2024 Virtual Summit On-Demand >
Learn Data, AI, and Integration Best Practices That Worked
This year’s Data + AI Integration Virtual Summit is focused on giving data/AI leaders across industries and data engineers the best practices that helped others modernize integration, make data AI-ready, and succeed with enterprise AI.
Learn how to scale data-driven strategy, technologies, teams, and processes.
See real-world examples across financial services, healthcare, and B2B.
Dive deep into how AI is being used to transform traditional processes across industries.
Learn the best practices from the experts that helped them succeed with GenAI.
Get the latest insights into open source AI projects, and what’s coming.
Dive into integration and GenAI best practices across Financial Services, Healthcare, Hospitality, Life sciences, and Retail.
Complete Agenda Coming Soon...
Check back for the exciting detailed agenda, which will break out sessions by topic and speaker!
Understand the core use cases of integration and AI for analytics, data science, B2B (intercompany), and operations.
Dive deep into the integration and AI best practices that worked, and some lessons learned the hard way.
Make sure your data is AI-ready, and your AI is ready for data. Understand what integration skills you need, how to compare LLMs, improve data quality and model accuracy, and accelerate GenAI projects.
Ideal for those overseeing strategic data initiatives and looking to address organization, governance, and technology challenges.
Tailored for data and AI engineering leaders looking to improve integration, AI, and governance team performance.
Ideal for lead engineers and managers looking for the data and AI engineering best practices, architectures, and technologies.
Suited for leaders in data usage roles who depend on data engineering for data movement and preparation.